09451401cc
- Updated vector store provider references throughout documentation - Changed default vector store from Qdrant to Supabase (pgvector) - Updated configuration examples to use Supabase connection strings - Modified navigation structure to remove qdrant-specific references - Updated examples in mem0-with-ollama and llama-index integration - Corrected API reference and architecture documentation 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
55 lines
2.5 KiB
Plaintext
55 lines
2.5 KiB
Plaintext
---
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title: Overview
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icon: "info"
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iconType: "solid"
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---
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<Snippet file="blank-notif.mdx" />
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Mem0 includes built-in support for various popular databases. Memory can utilize the database provided by the user, ensuring efficient use for specific needs.
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## Supported Vector Databases
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See the list of supported vector databases below.
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<Note>
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The following vector databases are supported in the Python implementation. The TypeScript implementation currently only supports Qdrant, Redis, Vectorize and in-memory vector database.
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</Note>
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<CardGroup cols={3}>
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<Card title="Qdrant" href="/components/vectordbs/dbs/qdrant"></Card>
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<Card title="Chroma" href="/components/vectordbs/dbs/chroma"></Card>
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<Card title="Pgvector" href="/components/vectordbs/dbs/pgvector"></Card>
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<Card title="Upstash Vector" href="/components/vectordbs/dbs/upstash-vector"></Card>
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<Card title="Milvus" href="/components/vectordbs/dbs/milvus"></Card>
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<Card title="Pinecone" href="/components/vectordbs/dbs/pinecone"></Card>
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<Card title="MongoDB" href="/components/vectordbs/dbs/mongodb"></Card>
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<Card title="Azure" href="/components/vectordbs/dbs/azure"></Card>
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<Card title="Redis" href="/components/vectordbs/dbs/redis"></Card>
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<Card title="Elasticsearch" href="/components/vectordbs/dbs/elasticsearch"></Card>
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<Card title="OpenSearch" href="/components/vectordbs/dbs/opensearch"></Card>
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<Card title="Supabase" href="/components/vectordbs/dbs/supabase"></Card>
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<Card title="Vertex AI" href="/components/vectordbs/dbs/vertex_ai"></Card>
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<Card title="Weaviate" href="/components/vectordbs/dbs/weaviate"></Card>
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<Card title="FAISS" href="/components/vectordbs/dbs/faiss"></Card>
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<Card title="LangChain" href="/components/vectordbs/dbs/langchain"></Card>
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</CardGroup>
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## Usage
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To utilize a vector database, you must provide a configuration to customize its usage. If no configuration is supplied, a default configuration will be applied, and `Supabase` (with pgvector) will be used as the vector database.
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For a comprehensive list of available parameters for vector database configuration, please refer to [Config](./config).
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## Common issues
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### Using model with different dimensions
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If you are using customized model, which is having different dimensions other than 1536
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for example 768, you may encounter below error:
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`ValueError: shapes (0,1536) and (768,) not aligned: 1536 (dim 1) != 768 (dim 0)`
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you could add `"embedding_model_dims": 768,` to the config of the vector_store to overcome this issue.
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